Differences in Occupations and Earnings

1
Differences in Occupations and Earnings

• Week 4 Class Notes

2
Definition Occupational Segregation

• Occupational segregation measures the extent to
  which men, women, and members of racial and
  ethnic groups are concentrated in certain
  industries or occupations.

3
Consequences of Occupational Segregation

• This concentration translates into systematically
  different labor market opportunities based on
  group membership, and
• operates as a precursor to differences in wages,
• differences in labor market mobility,
• differential opportunities for promotion,
• and other stratified labor market indicators.

4
Even Neoclassicals should care!

• Depending on the cause of the segregation,
  segregation can cause labor market rigidity and
  reduce economic efficiency (Anker, 1998)

5
Table 5.1 Distribution of Men and Women by Major
Occupation, 1972 and 1999
Occupation 1972 1999
Men () Women () Men () Women ()
Executive, administrative, and managerial 11.5 4.6 15.0 14.2
Professional specialty 9.7 12.4 13.6 18.0
Technicians and related support 2.3 2.4 2.9 3.6
Sales occupations 10.0 11.1 11.3 13.0
Administrative support, including clerical 6.4 31.5 5.5 23.4
Service Occupations 8.3 21.2 9.9 17.5
Precision production, craft, and repair 19.4 1.6 18.6 2.1
Operators, fabricators, and laborers 25.9 13.4 19.3 7.1
Farming, forestry, and fishing 6.4 1.9 3.8 1.1
Total employed 100.0 100.0 100.0 100.0
Segregation Index 41.8 32.3
6
Index of Segregation

• Index of segregation gives the percentage of
  female (or male) workers who would have to change
  jobs in order for the occupational distribution
  of the two groups to be the same.
• 0 if the dist of men and women across
  occupational categories were identical
• 100 if all occupations were completely male or
  female
• egregation index ½ the sum of absolute value of
  MI - FI
• MI percentage of males in the labor force
  employed in occupation I
• FI percentage of females in the labor force
  employed in occupation I

7
Table 5.2 Distribution of Men and Women by Major
Industry, 1972 and 1999
Industry 1972 1999
Men () Women () Men () Women ()
Agriculture 5.8 2.1 3.4 1.4
Mining 1.1 0.1 0.7 0.1
Construction 9.8 0.9 11.3 1.4
Manufacturing 28.2 17.9 19.1 10.4
Transportation and public utilities 8.6 3.6 9.5 4.4
Wholesale and retail trade 18.9 22.2 20.2 21.2
Finance, insurance, and real estate 4.3 6.9 5.2 8.2
Services 17.2 41.9 25.9 48.6
Public administration 6.1 4.2 4.6 4.3
Total employed 100.0 100.0 100.0 100.0
Segregation Index 30.7 26.7
8
Occ Seg by Race

• What are your guesses with regard to occupational
  segregation by race?

9
Vertical Segregation
Hierarchies within Occupations men and women
tend to be employed at different levels within
occupations vertical segregation
Academic Rank 1974-1975 1985-1986 1994-1995
Professor 10.1 11.6 16.2
Associate Professors 17.3 23.3 31.2
Assistant professors 27.9 35.8 44.7
Sources AAUP Bulletin, 61 (1975), Department of
Education (1992), Academe (1995)
10
Questions

• Is Occupational Segregation bad?
• What level of occupational segregation is optimal?

11
Trends in Occ Seg

• Studies show little change in degree of
  segregations in a number of decades prior to 1960
• 1960-1970 inflow of men into female professions
  and of women into male sales and clerical jobs
  produced a modest drop in seg index of 3.1
  percentage points
• 1970s and 1980s larger declines 7-8 percent
• 67.7 in 1970, 59.3 in 1980 and 52.0 in 1990
• Changes due to
• changes in the sex composition of individual
  occupations due to integration of previously male
  or female jobs
• shifts in occupation mix through increases in the
  size of integrated occupations relative to size
  of male and female jobs

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Differences in Earnings

• Definition The Wage Gap Wages(women)/Wages(men)
• Using this measure women who work full-time
  full-year round now earn about 77 of what men
  earn
• This is compared to 59 cents on the male dollar
  40 years ago

13
Table 5.7 Female-to-Male Earnings Ratios of
Full-Time Workers, Selected Years, 1955-1999
Year Annual Earnings of Full-Time Year Round Workers Usual Weekly Earnings of Full-Time Workers
1955 63.9
1960 60.8
1965 60.0
1970 59.4 62.3
1975 58.8 62.0
1980 60.2 64.4
1985 64.6 68.2
1990 71.6 71.8
1995 71.4 75.5
1999 76.5
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Table 5.8 Mean Earnings Ratios of FT, Year-Round
Workers by Age 1960-1999
Age 1960 1970 1980 1990 1999
25-34 65.1 64.9 68.5 76.9 76.4
35-44 57.6 53.9 55.3 64.4 65.6
45-54 58.0 56.3 52.0 58.2 59.6
55-64 64.5 60.3 54.9 57.1 58.6
BFW, page 147
15
Median Income of Men and Women Working
Year-Round, FT, by Years of Schooling, 1967 and
1995
1967 1999
Income Income Ratio () Income Income Ratio ()
Education Men () Women () Men() Women ()
Elementary 25,392 14,323 56.4 20,429 15,098 73.9
HS
1-3 years 31,443 16,901 53.8 25,035 17,015 68.0
4 years 35,280 20,528 58.2 33,184 23,061 69.5
College
1-3 years 40,226 23,969 59.6 39,971 28,826 72.1
4 years or more 52,797 31,009 58.7 60,201 41,747 69.3
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Year White F/M Black F/M Hispanic F/M Black-White M/M Black-White F/F Hispanic-White M/M Hispanic-White F/F
1955 65.3 55.1 Na 60.9 51.4 Na Na
1960 60.6 62.2 Na 66.1 67.8 Na Na
1965 57.9 62.5 Na 62.8 67.9 Na Na
1970 58.6 70.5 Na 68.1 81.9 Na Na
1975 57.5 75.1 68.6 73.2 95.5 71.2 85.0
1980 59.3 78.7 71.7 70.4 93.3 70.0 84.5
1985 64.1 81.2 78.0 70.0 88.5 67.5 82.0
1990 69.0 86.0 83.8 71.4 88.9 64.0 77.7
1995 71.3 83.2 89.6 72.8 85.0 61.2 75.9
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Table 5.3 Distribution of Workers by Occupation,
Race, Hispanic Origin, and Gender, 1999
Whites Blacks Hispanics
Occupation Men () Women () Men () Women () Men () Women ()
Exec, Admin, Mgmt 15.9 14.7 8.5 11.1 7.3 9.0
Professional specialty 13.6 18.7 9.5 13.5 5.3 9.1
Technicians and related sprt 2.9 3.6 2.7 3.5 1.7 2.5
Sales occupations 11.7 13.3 7.6 10.8 7.5 11.7
Admin support, clerical 5.1 23.6 8.1 23.9 5.7 22.6
Service occupations 8.9 16.2 17.4 25.6 14.9 26.7
Precision production craft and repair 19.4 2.1 14.3 2.1 21.2 2.8
Operators, fabricators, and laborers 18.3 6.5 29.8 9.4 27.8 13.6
Farming, forestry, and fishing 4.1 1.2 2.2 0.2 8.6 1.8
Total Employed 100 100 100 100 100 100
Segregation indices
By sex 33.2 34.6 39.3
By race/ethnicity (compared to whites) na na 23.1 13.3 21.7 17.9
18
Table 9.3 Jacobsen Non-agricultural hourly
earnings ratios, developed and developing
countries
Country Women/Men Country Women/Men
Iceland 0.93 Botswana 0.97
Sweden 0.90 Turkey 0.97
Australia 0.89 Myanmar 0.96
Norway 0.88 El Salvador 0.95
Denmark 0.83 Kenya 0.94
New Zealand 0.83 Philippines 0.90
France 0.82 Cook Islands 0.89
United Kingdom 0.80 Sri Lanka 0.85
Finland 0.79 Egypt 0.81
Belgium 0.79 Costa Rica 0.79
Netherlands 0.77 Mexico 0.76
United States 0.76 Brasil 0.75
Ireland 0.75 Paraguay 0.74
Germany 0.74 Thailand 0.72
Luxembourg 0.70 Swaziland 0.64
Austria 0.69 Cyprus 0.64
Switzerland 0.67 Malaysia 0.63
South Korea 0.64 Eritrea 0.58
Japan 0.64 Macau 0.56
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Problems with this measure

• Wages hourly? Weekly? Monthly?
• Whose wages?
• What work?
• Mean or Median?

20
Rose and Hartmanns Measurement

• How should we measure the gender gap? By
  focusing just on those with the strongest labor
  force attachment or just on hourly earnings in a
  single week or year, one is tacitly accepting the
  constraints of current gender relationships. All
  of the women who make the constrained choice to
  work part-time or to take time off for family
  care are excluded from the comparisons

21
Rose and Hartmanns Measure

• Long-term perspective on the wage gap 15 year
  average approximation of permanent income

22
Ranges of the Rose and Hartmann Wage Gap Measure

• 62 based on the annual average earnings of all
  the men and women in the sample, including their
  zero-earnings years in the average
• 57 based on the annual earnings of everyone in
  the sample, but excluding their zero-earnings
  years
• 44 based on the annual earnings of those women
  and men with at least some earning every year
  (the strongly attached)
• 36 based on the annual earnings of women and men
  with no labor force interruptions who also worked
  persistently full-time full-year (the super
  attached)

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Note Men Work More Hours

• Even among the super attached, but even when
  adjusting for hours worked men earn more.
• 35 adjusted for hours worked across all earnings
  years for all women and men with at least one
  non-zero earnings year
• 28 adjusted for hours worked for only those
  workers with earnings in every year of the 15
  year study

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Explaining Differences in Earnings

• Supply Side Factors What people BRING to the
  labor market
• Human Capital Model
• Differences in Choices Occupation and Hours,
  (innate differences, socialized differences and
  babies)
• Demand Side Factors What people FACE once they
  get to the labor market
• Differences in Demand for Men and Women?
• Discrimination?

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The Human Capital Model

• Definition
• Education
• Experience
• The Model

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Occupational Segregation

• Is it a Cause or a Consequence of the Wage Gap?
• According to Rose and Hartmann women and men
  work different amounts of time, they work in
  different types of jobs and they are paid
  differently even when they have similar levels of
  education

27
More on Rose, Hartmann and Occ Seg

• workers of seemingly similar abilities get
  paid differently depending on what job they have
  and what company they work for. These differences
  are generally larger than could be accounted for
  by differences in workers preferences

28
More ways that ones job affects ones wages. . .
And that differences is gendered

• Firms dont exist in a perfectly competitive
  vacuum. Why does this matter? There are barriers
  to entry that reduce competition.
• The relationship that a company has with its
  employees is complex.

29
Rose and Hartmanns Conclusion?

• For most industries and workers, earnings are
  connected to social norms.

30
Gender differences in the workplace are revealed
in several ways by data on occ seg

1. Women and men do indeed hold and remain in
   different clusters of jobs in the LM
2. Regardless of the level or tier of the jobs or
   whether one is looking at the female or male job
   clusters at that level, women earn substantially
   less than men, even considering only full-time
   work

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More

• 3. Both men and women earn more in the male
  sector of each tier than their counterparts do in
  the female sector in the same tier, indicating a
  premium for working in male-type jobs, and,
  conversely, a penalty for working in female-type
  jobs
• 4. The male sector generally requires more hours
  of work than the female sector
• And
• 5. When men work in the female sector they earn
  more than women. When women work in the male
  sector they earn more than they would have, but
  still less than men in that sector.

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Womens Choices as an Explanation

• Were back to choice feminism!
• Causes of the wage gap and occupational
  segregation Choice? Hours/Flexibility/type of
  work?
• Socialization? (but is that choice?)

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Table 7.1 Average Characteristics of Full-Time
Workers, 1989, Ages 18-65
Men Women
Years of education 13.37 13.38
Proportion with college degree 0.20 0.19
Proportion with advanced degree 0.08 0.07
Years of full-time experience 17.41 12.79
Years of part-time experience 1.61 2.46
Proportion white 0.92 0.89
Proportion in following occupations
Managers 0.19 0.12
Professionals and technical 0.20 0.30
Clerical 0.04 0.31
Sales 0.05 0.03
Craft 0.24 0.01
Operators 0.19 0.10
Service or laborers 0.10 0.13
Proportion in following industries
Mining, construction, durable manuf. 0.30 0.11
Nondurable manuf 0.10 0.08
Transportation 0.12 0.04
Wholesale trade 0.06 0.02
Retail trade 0.10 0.12
Finance, insurance, real estate 0.04 0.11
Services 0.19 0.45
Government 0.09 0.06
Proportion unionized 0.22 0.17
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Empirical Evidence Explanation of the Wage Gap
what explains most?

• The following table is the result of a wage gap
  decomposition that attempts to disentangle the
  supply and demand-side causes of the wage gap

35
Table 7.2 Percentages of the Wage Differential
between Men and Women Explained by Differences
in Measured Characteristics, 1988
Characteristics Human Capital Variables Only All Variables
Educational attainment 0.3 0.3
Labor Force Experience 30.8 26.2
Race 1.8 1.2
Occupational category -- 7.8
Industrial Category -- 22.6
Union Status -- 3.8
Unexplained 67.1 38.0
Total 100.0 100.0
Wage Differential () 27.6 27.6
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Whats Left-Over?

• The Demand Side Discrimination

37
Problems with that Methodology?

• we have no info on all the qualifications of
  individuals associated with potential
  productivity. EX motivation, work effort,
  college major
• if men are more highly qualified wrt the factors
  that are omitted from the analysis, the extent of
  LM discrimination is likely to be overestimated.
• some of the lower qualifications of women may be
  a direct result of LM disc. EX a qualified woman
  may be excluded from participation.
• Neglect feedback effects of LM disc on the
  behavior and choices of women themselves